ReviewCureus2024
Early Diagnosis of Cardiovascular Diseases in the Era of Artificial Intelligence: An In-Depth Review.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- A multi-view autoencoder architecture with self-adaptive feature recalibration and confidence-aware ensemble for heart disease classification.Scientific reports · 2026Article
- Review
- Cardiovascular digital twins using a Windkessel physics informed neural network.NPJ digital medicine · 2026Article
- Clinical Applications of Artificial Intelligence in Cardiovascular Imaging: Where Do We Stand?Life (Basel, Switzerland) · 2026Review
- Considerations for the Adoption of Digital Algorithms and Cardiovascular Decision-Support Tools in Clinical Practice.Critical pathways in cardiology · 2026Review
- Artificial Intelligence in African Cardiovascular Care: Opportunities, Challenges, and Pathways to Improved Outcomes.Public health challenges · 2026Review
- Prediction of carotid vulnerable plaques in patients with type 2 diabetes using interpretable machine learning models.Frontiers in endocrinology · 2026Article
- Risk prediction for cardiovascular related diseases using PRS and EHR in the Framingham Heart Study.PloS one · 2026Article
- Exploring multimodal large language models on transthoracic Echocardiogram (TTE) tasks for cardiovascular decision support.Journal of biomedical informatics · 2025Article
- Diagnostic Accuracy of AI-Assisted Focused Cardiac Ultrasound (FOCUS) in Primary Care.Healthcare (Basel, Switzerland) · 2025Article
- The Use of Artificial Intelligence in ECG Interpretation in the Outpatient Setting: A Scoping Review.Cureus · 2025Review
- Multimodal AI in Biomedicine: Pioneering the Future of Biomaterials, Diagnostics, and Personalized Healthcare.Nanomaterials (Basel, Switzerland) · 2025Review
- Review
- Functionalized screen-printed electrodes for non-invasive detection of vascular-endothelial cadherin in extracellular vesicles.RSC advances · 2025Article
- Bibliometric analysis of artificial intelligence applications in cardiovascular imaging: trends, impact, and emerging research areas.Annals of medicine and surgery (2012) · 2025Article
- Artificial Intelligence and Heart-Brain Connections: A Narrative Review on Algorithms Utilization in Clinical Practice.Healthcare (Basel, Switzerland) · 2024Review
- Revolutionizing Cardiology through Artificial Intelligence-Big Data from Proactive Prevention to Precise Diagnostics and Cutting-Edge Treatment-A Comprehensive Review of the Past 5 Years.Diagnostics (Basel, Switzerland) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular diseases (CVDs) are significant health issues that result in high death rates globally. Early detection of cardiovascular events may lower the occurrence of acute myocardial infarction and reduce death rates in people with CVDs. Traditional data analysis is inadequate for managing multidimensional data related to the risk prediction of CVDs, heart attacks, medical image interpretations, therapeutic decision-making, and disease prognosis due to the complex pathological mechanisms and multiple factors involved. Artificial intelligence (AI) is a technology that utilizes advanced computer algorithms to extract information from large databases, and it has been integrated into the medical industry. AI methods have shown the ability to speed up the advancement of diagnosing and treating CVDs such as heart failure, atrial fibrillation, valvular heart disease, hypertrophic cardiomyopathy, congenital heart disease, and more. In clinical settings, AI has shown usefulness in diagnosing cardiovascular illness, improving the efficiency of supporting tools, stratifying and categorizing diseases, and predicting outcomes. Advanced AI algorithms have been intricately designed to analyze intricate relationships within extensive healthcare data, enabling them to tackle more intricate jobs compared to conventional approaches.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.